A Monte Carlo Methodology for Solving the Optimal Timber Harvest Problem with Stochastic Timber and Carbon Prices
Abstract
This article presents a Monte Carlo methodology for solving the
stochastic optimal timber harvest problem modeled as a recurrent
American call option. A detailed description of the proposed method-
ology is given, and the Monte Carlo technique is contrasted with finite
difference methods typically used to find solutions of the optimal har-
vest problem with stochastic prices. The use of the methodology is
then demonstrated via an example. In the example, expected bare
land values and optimal harvest policies are calculated for a Douglas-
fir stand in western Washington State. It is assumed that the forest
owner derives revenue from traditional timber sales and carbon seques-
tration, and that prices of timber and carbon follow a known stochastic
process. Results of the calculations are discussed. MCFNS 2(2):67-77.
stochastic optimal timber harvest problem modeled as a recurrent
American call option. A detailed description of the proposed method-
ology is given, and the Monte Carlo technique is contrasted with finite
difference methods typically used to find solutions of the optimal har-
vest problem with stochastic prices. The use of the methodology is
then demonstrated via an example. In the example, expected bare
land values and optimal harvest policies are calculated for a Douglas-
fir stand in western Washington State. It is assumed that the forest
owner derives revenue from traditional timber sales and carbon seques-
tration, and that prices of timber and carbon follow a known stochastic
process. Results of the calculations are discussed. MCFNS 2(2):67-77.
Keywords
Optimal Harvest; American Option; Monte Carlo; Carbon Sequestration
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